Survey: GraphRAG and Knowledge Graphs for Large Language Models

Papers Survey

The seminal paper “Unifying Large Language Models and Knowledge Graphs: A Roadmap” published on June 14, 2023, presents a comprehensive framework for integrating the emergent capabilities of Large Language Models (LLMs) with the structured knowledge representation of Knowledge Graphs (KGs)  Authored by Shirui Pan, Linhao Luo, Yufei Wang, Chen Chen, Jiapu Wang, and Xindong Wu, […]

Ultra-fast, multi-tenant graph database using sparse matrix representations and linear algebra, ideal for highly technical teams that handle complex data in real-time, resulting in fewer hallucinations and more accurate responses from LLMs.

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Simply ontology creation, knowledge graph creation, and agent orchestrator

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Ultra-fast, multi-tenant graph database using sparse matrix representations and linear algebra, ideal for highly technical teams that handle complex data in real-time, resulting in fewer hallucinations and more accurate responses from LLMs.

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Avi Tel-Or

CTO at Intel Ignite Tel-Aviv

I enjoy using FalkorDB in the GraphRAG solution I'm working on.

As a developer, using graphs also gives me better visibility into what the algorithm does, when it fails, and how it could be improved. Doing that with similarity scoring is much less intuitive.

Dec 2, 2024

Ultra-fast, multi-tenant graph database using sparse matrix representations and linear algebra, ideal for highly technical teams that handle complex data in real-time, resulting in fewer hallucinations and more accurate responses from LLMs.

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